# Copyright (c) OpenMMLab. All rights reserved.
# dataset settings
_base_ = 'coco_instance.py'
dataset_type = 'LVISV1Dataset'
data_root = 'data/lvis_v1/'
data = dict(samples_per_gpu=2,
            workers_per_gpu=2,
            train=dict(_delete_=True,
                       type='ClassBalancedDataset',
                       oversample_thr=1e-3,
                       dataset=dict(type=dataset_type,
                                    ann_file=data_root +
                                    'annotations/lvis_v1_train.json',
                                    img_prefix=data_root)),
            val=dict(type=dataset_type,
                     ann_file=data_root + 'annotations/lvis_v1_val.json',
                     img_prefix=data_root),
            test=dict(type=dataset_type,
                      ann_file=data_root + 'annotations/lvis_v1_val.json',
                      img_prefix=data_root))
evaluation = dict(metric=['bbox', 'segm'])
